Market-government dual-driven framework for reliability-centric planning of a computation-energy integrated system with data centers

Chen Liang, Bo Zeng, Yueyi Lei and Yuan Wang

Applied Energy, 2025, vol. 396, issue C, No S0306261925010025

Abstract: The rapid development of Computation-Energy Integrated Systems (CEIS) has highlighted the urgent need to improve system reliability, particularly as these centers integrate with power grids (PGs) and heating networks (HNs). Achieving high reliability, however, cannot be fully realized through market efforts alone to align all stakeholders. This paper proposes a novel market-government dual-driven framework for the coordinated planning of data centers (DCs), PGs, and HNs, ensuring the high-reliability transition of CEIS. The framework is based on a three-level hierarchical optimization model that integrates market signals and government incentives to encourage decentralized, reliable decision-making. The upper level makes investment decisions for DCs, PGs, and HNs based on profit maximization. The middle level employs market mechanisms to enhance the reliability of scheduling, while the lower level addresses fault scenarios, integrating energy and information domain failures and combining government-driven incentives to improve reliability. By incorporating flexibility from the information domain, particularly from DCs, the framework significantly enhances energy system stability, offering considerable benefits under fault conditions. Moreover, the combination of market signals and government incentives provides a robust solution to the reliability challenges faced by highly integrated urban CEIS. Numerical studies demonstrate that this dual-driven framework outperforms traditional centralized models in reducing load curtailment and improving system resilience, achieving a fault-induced load curtailment rate of 93.89 % and a self-sufficiency rate of 82.34 %.

Keywords: High-reliability; Computation-energy integrated system; Data center; Fault operation; Coordinative planning; Dual-driven (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2025.126272

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